We prove an analog of the removable singularity theorem for bounded harmonic functions on stratified sets. The harmonic functions are understood in the sense of the soft Laplacian. The result can become one of the main technical components for extending the well-known Poincaré–Perron’s method of proving the solvability of the Dirichlet problem for the soft Laplacian.

This study extends the CGAN-based MODIS cloud vertical-profile (64×64-scene, about 70km width×15km height) retrieval technique developed by Leinonen et al. (2019) [1] to construct seamless 3D cloud fields for the MODIS granules [2]. Firstly, the accuracy and spatial continuity of the Leinonen et al. [1] retrievals are statistically evaluated. Then, according to the characteristics of the retrieval error, a spatially overlapping-scene ensemble generation method and a bi-directional Ensemble Binning Probability Fusion (CGAN-BEBPF) technique are developed, which improves the CGAN retrieval accuracy and support to construct seamless 3D clouds. The CGAN-BEBPF technique involves three steps: cloud masking, intensity scaling, and optimal value selection. It ensures adequate coverage of the low reflectivity areas while preserving the high reflectivity cloud cores. The technique is applied to retrieve the 3D cloud fields of Typhoon Chaba and a multi-cell convective system. The cloud structures of the CGAN-BEBPF results are highly consistent with the ground-based radar observations. It can retrieve weak clouds at the top levels of convective storms and hurricanes that were missed by ground-based radars and fill the gaps of the ground-based radar lower-level PPI scan. Overall, CGAN-BEBPF can be automated to retrieve the rich informative 3D structures of typhoons and severe convective systems over the oceans along the MODIS swath, which certainly presents great value for improving maritime and near-shore typhoons and convection prediction and other cloud-sensitive applications.

Active flow control is a promising technology for reducing noise, emissions, and power consumption in various applications. To better understand the performance of synthetic jet actuators, a computational model that couples structural mechanics with electrostatics, pressure acoustics, and fluid dynamics has been needed. The model presented here has been validated against experimental data and then used to investigate the fluid behavior inside and outside the synthetic jet actuator cavity, impacts of thermoviscous losses on capturing the acoustic response of the actuator, and viability of different modeling methods of diaphragms in computational simulations. The results capture the feedback from the fluid onto the diaphragm and highlight the need for careful acoustic modeling.

Rubella infection is typically mild or asymptomatic except when infection occurs during pregnancy. Infection in early pregnancy can cause miscarriage, stillbirth, or congenital rubella syndrome. Only individuals that are still susceptible to rubella infection during child-bearing age are vulnerable to this burden. Rubella containing vaccine (RCV) is safe and effective, providing life-long immunity. However, average age-at-infection increases with increasing vaccination coverage, which could potentially lead to increased disease burden as well, if the absolute risk of infection during child-bearing age increases. Dynamics of rubella transmission were explored using EMOD, a software tool for building stochastic, agent-based infection models. Simulations of pre-vaccine, endemic transmission of rubella virus introduced RCV at varying levels of coverage to determine the expected future trajectories of disease burden. Introducing RCV reduces both rubella virus transmission and disease burden for a period of around 15 years. Increased disease burden is only possible more than a decade post-introduction, and only for contexts with low current burden and high transmission intensity. Low or declining rubella virus transmission intensity is concurrently associated with both greater disease burden and greater vaccine effectiveness. The risk of increasing burden through vaccination only exists for locations with persistently high infectivity, high connectivity, and high fertility. A trade-off between the risk of a small, future burden increase and a large, immediate burden decrease strongly favors RCV introduction.

In the field of computational fluid dynamics (CFD) for rotorcraft, two significant challenges are resolving the complex vortex structures in rotor wakes, and representing the moving rotor blades in the ambient airflow. This study addresses the first challenge by using a third-order unstructured finite volume solver, which, compared to its second-order counterpart, has substantially lower dissipation. Consequently, even relatively coarse meshes are capable of resolving small vortices. With this background flow field solver, the second challenge is addressed by modeling each rotor as an Actuator Disk Model (ADM), or describing individual rotor blades as actuator lines, designated as the Actuator Line Model (ALM). Both of these models are equipped with an improved correction for aerodynamic losses at blade tips, which is thoroughly presented in the methodology section. The numerical experiments section centers on analyzing errors linked to various sampling approaches. Additionally, the article discusses comparisons between vortex theory and ALM, specifically regarding calculations for fixed-wing aircraft. Furthermore, high-order precision and parallel efficiency are exemplified in scenarios encompassing rotors engaged in both hovering and forward flight rotors. The results in this paper demonstrate that the combination of the ALM/ADM with the improved tip loss correction and the third-order finite volume solver presents a new way of developing efficient tools for the aerodynamic analysis of helicopter rotors.

In order to coordinate the damping performance and energy regenerative performance of energy regenerative suspension, this paper proposes a structure of vehicle semi-active energy regenerative suspension with electro-hydraulic actuator (EHA). In light of the proposed concept, a specific energy regenerative scheme is designed and the mechanical properties test is carried out. Based on the test results, the parameter identification for the system model is conducted using recursive least squares algorithm. On the basis of system principle, the nonlinear model of the semi-active energy regenerative suspension with EHA is built. Meanwhile, LQG control strategy of the system is designed. And then the influence of the main parameters of EHA on the damping performance and energy regenerative performance of suspension is analyzed. Finally, the main parameters of EHA actuator are optimized via genetic algorithm. The test results show that when sinusoidal is input at the frequency of 2Hz and the amplitude of 30mm, the spring mass acceleration RMS value of optimized EHA semi-active energy regenerative suspension is reduced by 22.23% and energy regenerative power RMS value is increased by 40.51%, which means while meeting the requirements of certain vehicle ride comfort and driving safety, energy regenerative performance is improved significantly.

Computational fluid dynamics is used to study the impact of the support structure of a tidal turbine on performance and the downstream wake characteristics. A high-fidelity computational model of a dual rotor, contra-rotating tidal turbine in a large channel domain is presented, with turbulence modelled using large eddy simulation. Actuator lines represent the turbine blades, permitting the analysis of transient flow features and turbine diagnostics. The following four cases are considered: the flow in an unexploited, empty channel; flow in a channel containing the rotors; flow in a channel containing the support structure; and flow in a channel with both rotors and support structure. The results indicate that the support structure contributes significantly to the behaviour of the turbine and to turbulence levels downstream, even when the rotors are upstream. This implies that inclusion of the turbine structure, or some parametrisation thereof, is a prerequisite for the realistic prediction of turbine performance and reliability, particularly for array layouts where wake effects become significant.

Building defects are very prevalent and contribute significantly to a building's economic value. There are numerous information sources on building defects that have a lot potential for learning more about building defects. This study aimed to identify the information sources used in previous building defect studies and to identify the motivation for carrying out such studies. To fulfil this aim a scoping study was carried out. The information sources identified included insurance companies, private databases, questionnaire surveys, lawsuits, building surveys, client complaint forms, and maintenance reports. This study found that insurance company and client complaint forms include the largest collection of real building defect cases, but such databases may lack detailed descriptions of the causes of the defects. The main purposes of building defects studies identified here included design challenges, identification of defects, building maintenance management, quality management, systematization in data collection, providing an overview of typical defects, and classifying defects. Identification was found to be the most common purpose, indicating that the industry wants to learn more. This study identified research gaps in the climate perspective in relation to building defects. Most of the studies focused on the economical perspective, and none focused on the carbon footprint perspective.

The effective macroscopic model describing interactions of a viscous compressible heat-conducting fluid and a two-level fine bristly thermoelastic structure is derived from microstructure by means of the Allaire–Briane multi-scale convergence method. This new model naturally generalizes the isothermal formulation earlier constructed by the authors in 2020, see in Siberian Electronic Mathematical Reports, vol. 17 (https://doi.org/10.33048/semi.2020.17.100). In applications, the established model can be used, for example, in description, with account of heat transfer phenomemon, of airflow near surface of plant’s leaf, in simulation of epithelium surfaces of blood vessels, and in design of biotechnological devices operating in liquids.

Estimating ground surface PM2.5 with fine spatiotemporal resolution is a critical technique for exposure assessments in epidemiological studies of its health risks. Previous studies have utilized monitoring, satellite remote sensing or air quality modeling data to evaluate the spatiotemporal variations of PM2.5 concentrations, but such studies rarely combined these data simultaneously. We develop a three-stage model to fuse PM2.5 monitoring data, satellite-derived aerosol optical depth (AOD) and community multi-scale air quality (CMAQ) simulations together and apply it to estimate daily PM2.5 at a spatial resolution of 0.1˚ over China. Performance of the three-stage model is evaluated using a cross-validation (CV) method step by step. CV results show that the finally fused estimator of PM2.5 is in good agreement with the observational data (RMSE = 23.00 μg/m^3 and R2 = 0.72) and outperforms either AOD-retrieved PM2.5 (R2 = 0.62) or CMAQ simulations (R2 = 0.51). According to step-specific CVs, in data fusion, AOD-retrieved PM2.5 plays a key role to reduce mean bias, whereas CMAQ provides all-spacetime-covered predictions, which avoids sampling bias caused by non-random incompleteness in satellite-derived AOD. Our fused products are more capable than either CMAQ simulations or AOD-based estimates in characterizing the polluting procedure during haze episodes and thus can support both chronic and acute exposure assessments of ambient PM2.5. Based on the products, averaged concentration of annual exposure to PM2.5 was 55.75 μg/m3, while averaged count of polluted days (PM2.5 > 75 μg/m3) was 81, across China during 2014. Fused estimates will be publicly available for future health-related studies.

The fractional advection-dispersion equation FADE plays an important role, especially in explaining the process of solute-transport in natural porous media with different degrees of heterogeneity. However, studies of the flow and transport of contaminants in the underground environment are based on the knowledge of many functional parameters of the subsoil. The delay factor caused by nonlinear absorption is one of these parameters inheriting significant ambiguities in its estimation in heterogeneous media. In the study, a fractional advection-dispersion FADE model was developed by the implicit Euler method, based on a Grunwald and Caputo-Liousville approximation to explicitly evaluate and simulate the transport mechanism of contaminants in media with unsaturated porous materials subjected to a nonlinear sorption model. Better solute mass retention was observed for fractional advection-dispersion FADE model. Moreover, the absorption parameter of the retardation coefficient has a better impact on the motion of the solute in a saturated porous medium. In other words, it has a significant effect on the dispersion of pollutants in aquifers. This study highlights the need to characterize the aquifer to predict solute transport in porous media.

This study aims to investigate the psychological cognitive mechanisms of rural residents amidst the renewal of suburban historical and cultural villages by examining the interplay between nostalgia, collective memory, subjective well-being and place identity in rural tourism destinations. Using Naobao Village as a case study—a suburban historical and cultural village in Hohhot, Inner Mongolia, this research employs a comprehensive approach integrating experimental methods and questionnaire surveys. The findings demonstrate that analyzing the interaction among the four emotions can elucidate the psychological cognitive mechanism of residents. Moreover, it uncovers that tourism effects significantly influence residents' perception of their living environment with positive effects on collective memory, subjective well-being and place identity. In the theoretical model for generating psychological cognition among residents in suburban historical and cultural villages, subjective well-being and collective memory play crucial mediating roles. This study provides a theoretical foundation and practical guidance for spatial reconstruction and cultural evolution of tourist landscapes in suburban rural tourist destinations.

This review is focused on the current status of quantitative MR (qMR) of skeletal muscle. The first section covers the techniques of qMR in muscle with the focus on each quantitative parameter, the corresponding imaging sequence, discussion of the relation of the measured parameter to underlying physiology/ pathophysiology, the image processing and analysis approaches, and studies on normal subjects. We cover the more established parametric mapping from T1 weighted imaging for morphometrics including image segmentation, proton density fat fraction, T2 mapping, diffusion tensor imaging to emerging qMR features such as magnetization transfer including ultralow TE imaging for macromolecular fraction, and strain mapping. The second section is a summary of current clinical applications of qMR of muscle; the intent is to demonstrate the utility qMR in different disease states of the muscle rather than a complete comprehensive survey.

This paper is devoted to the study of multi-dimensional integral transform with Fox H-function in the kernel in weighted spaces integrable functions in the domain R+n with positive coordinates. Mapping properties such as the boundedness, the range, the representations of the considered transformation are established.

Hypertension is a global public health challenge, with a high prevalence across various regions and significant implications for cardiovascular risk. This article reviews the effectiveness of herbal medicine as a potential therapeutic approach for hypertension, offering an alternative or complementary solution to conventional pharmacological treatments. It highlights several natural agents that have demonstrated efficacy in lowering systolic blood pressure (SBP) in clinical and meta-analytical studies. The methodology involved a systematic review of articles that discuss herbal therapeutics for hypertension, focusing on their efficacy compared to placebo and standard treatments. The findings suggest that certain nutraceuticals, such as garlic, hawthorn, and CoQ10, can significantly reduce SBP, presenting a viable option for managing hypertension. This review underscores the need for further research to validate these findings and optimize herbal treatment strategies, potentially expanding the use of these natural products in clinical practice. The article aims to increase awareness among medical professionals and patients about the benefits and applications of herbal medicines in treating hypertension.

Reducing and time-shifting household energy demand is important for a sustainable transition of energy systems, and dynamic electricity pricing, like real-time pricing (RTP), is a popular instrument to incite households to change energy demand. However, the effect of such products relies on the assumption that dynamic price signals incorporate into everyday routines and rhythms. This paper investigates the flexibility of households’ everyday routines and rhythms. The study provides three insights based on 11 Danish household visits and interviews with electricity customers who are new to RTP. First, the interviews indicated confusion over terminology for dynamic pricing products and low interest in flexible energy demand. Second, everyday practices (already) appeared flexible but for other reasons than energy demand flexibility. Third, energy habits were important for providing meaning to everyday practices. In addition, the study shows that energy flexibility is not just about energy demand, but rather about all the other activities that form routines and rhythms in everyday life. We suggest 1) designing products that reflect ‘natural’ or ‘societal’ daily rhythms, 2) focusing on the engaged households, and 3) being aware that for some households, changes in pricing, including new payment schemes, might put extra pressure on already harried everyday routines.

In this paper we suggest a first ever construction of fractional integral and differential operators based on signed measures including a vector-valued case. The study focuses on constructing the fractional power of the Riemann-Stieltjes integral with a signed measure, using semigroup theory. The main result is a theorem that provides the exact form of a semigroup for the Riemann-Stieltjes integral with a measure having a countable number of extrema. The article provides examples of semigroups based on integral operators with signed measures and discusses the fractional powers of differential operators with partial derivatives.

We present a design of electrostatic comb driver to improve and investigate its actuation performance. The proposed electrostatic comb actuator (ECA) is composed of two set of interdigitated comb microstructures, the inner combs are fixed to form the fish-bone microstructures and the outer combs are movable and connected to crab-leg flexure beams microstructures. The ECA is investigated to optimize the actuation performance by changing the comb shape and the intersection angle of crab-leg flexure beams. The comb shapes are compared between the traditional rectangle shape and the trapezoid shape, while the intersection angles of crab-leg flexure beams are compared between 45°, 60°, and 90° on the influences of ECA displacement and stability characteristics. These parameters are investigated for their impacts on the dynamic comb displacement and driving voltage. Under the condition of a driving DC bias voltage of 100 volts, the ECA displacement is firstly increased and then gradually decreased by increasing the comb finger length. The maximum displacement of ECA with trapezoid comb is 47.2 μm while that of ECA with rectangle comb is 22.4 μm. By using trapezoid comb shape to replace the rectangle comb under the same conditions, the ECA displacement is improved 2-fold. To enhance the stability of ECA system, the intersection angle of 90˚ of crab-leg flexure beams shows highest stability that is great better than the intersection angle of 45° and 60° of crab-leg flexure beams by increasing the driving different DC bias voltage to 100 volts on ECA. The stability of the ECA with the intersection angle of 90° of crab-leg flexure beams is enhanced 1.1-fold and 1.4-fold compared to that of 45° and 60° of crab-leg flexure beams, respectively. This design provides an optimized approach to the electrostatic comb actuator that can be used expansively in the gyroscope, motion sensor, position sensor, imaging sensor, optical sensor, and so on.

Conditions under which compositions of component systems form a well-defined system-of-systems here are formulated at a fundamental level. Statement of what defines a well-defined composition and sufficient conditions guaranteeing such a result offers insight into exemplars that can be found in special cases such as differential equation and discrete event systems. For any given global state of a composition, two requirements can be stated informally as: 1) the system can leave this state, i.e., there is at least one trajectory defined that starts from the state, and 2) the trajectory evolves over time without getting stuck at a point in time. Considered for every global state, these conditions determine whether the resultant is a well-defined system and if so, whether it is non-deterministic or deterministic. We formulate these questions within the framework of iterative specifications for mathematical system models that are shown to be behaviorally equivalent to the Discrete Event System Specification (DEVS) formalism. This formalization supports definitions and proofs of the afore-mentioned conditions. Implications are drawn at the fundamental level of existence where the emergence of a system from an assemblage of components can be characterized. We focus on systems with feedback coupling where existence and uniqueness of solutions is problematic.

Sustainable water resource management in Bangladesh's Gumti River Basin faces challenges from climate change, urbanization, and population growth. This study aimed to calibrate and validate the HEC-HMS model for the Gumti River to enhance flood prediction and water resource planning. The model was set up using precipitation, temperature, and discharge data from 2019-2021, with SRTM elevation data for catchment delineation. Manual calibration was performed for 2019-2020, followed by validation for 2021, using parameters such as Muskingum routing and SCS Curve Number. Model performance was evaluated using R², Nash-Sutcliffe efficiency (NSE), RSR, and PBIAS metrics. Results showed satisfactory to good performance, with R² values of 0.64 and 0.68 for calibration and validation, respectively. NSE values were within the satisfactory range, while PBIAS indicated very good performance with slight underestimation. The study concludes that the calibrated HEC-HMS model provides a reliable tool for simulating the Gumti River's hydrology, though there's room for improvement. Integration with flood frequency analysis, water quality monitoring, and climate change projections is recommended for comprehensive water resource management, alongside the implementation of Sustainable Water Resource Management principles and community engagement strategies.

Context. During the COVID-19 pandemic, patient care was mainly organised around the hospital. Pre-hospital care has, to our knowledge, never been evaluated. Objective: To evaluate the impact of pre-hospital pathways on hospitalisation during the last part of the pandemic. Design. This was a monocentric retrospective analysis of prospectively collected medical records. Data from patients admitted to our institute between 1 February and 7 March 2022 were analysed. Main Outcome Measure(s): The primary outcomes were defined as the number of hospitalisations, resuscitations, and deaths at the time of interview and in the subsequent 30 days. The main explanatory variables were times from onset of symptoms to care, age, gender, News2 score, comorbidities, and pre-hospital pathways and their duration. Results: Three pre-hospital pathways have been identified: a pathway in which the patient consults a general practitioner for a test (PHP1); a pathway in which the patient consulted for care (PHP2); and no pre-hospital pathway and direct admission to hospital (PHP3). Factors independently associated with outcome (hospitalisation) were being male (OR 95% CI; 2.21 [1.01–4.84], p=0,04), News2 score (OR 95% CI; 2.04 [1.65–2.51], p<0.001), obesity (OR 95% CI; 3.45 [1.48–8.09], p=0.005), D-dimers > 0.5 µg/ml (OR 95% CI; 3.45 [1.47–8.12], p=0.005), prolonged time from symptoms to hospital care (PHP duration) (OR 95% CI; 1.07 [1.01–1.14], p=0.03). All things being equal, patients with a “PHP2” pre-hospital pathway had a higher probability of hospitalisation compared to those with a “PHP3” pre-hospital pathway (OR 95% CI; 4.31 [1.48–12.55], p=0.007). Conclusions. Along with recognised risk factors such as gender, News 2 score, and obesity, the patient’s pre-hospital pathway is an important risk factor associated with hospitalisation.

This manuscript compares deterministic artificial intelligence to model following control applied to DC motor control, including evaluation of the threshold computation rate to let unmanned underwater vehicles correctly follow the challenging discontinuous square wave command signal. The approaches presented in the main text are validated in MATLAB®, where the motor process is discretized at multiple step sizes, which is inversely proportional to the computation rate. The performance is evaluated by the error mean and standard deviation. With a large step size, discrete deterministic artificial intelligence shows a larger error mean than the model-following self-turning regulator approach (benchmark selection). However, the performance gets optimized with the step size decreased. The error mean is close to the continuous deterministic artificial intelligence when the step size is reduced to 0.2 seconds, which means that the computation rate and the sampling period restrict discrete deterministic artificial intelligence. In that case, the continuous deterministic artificial intelligence is the most feasible and reliable selection for future applications on unmanned underwater vehicles since it is superior to all the approaches with multiple computation rates.

High hepcidin is linked to low-grade inflammation and lower iron levels. The consequence of testosterone replacement therapy (TRT) on inflammation and risk of cardiovascular disease (CVD) is undetermined. We investigate the effect of TRT on the inflammatory cardiovascular risk markers hepcidin-iron, fibroblast growth factor 23 (FGF23)-phosphate-klotho, and calprotectin pathways. Methods: A randomized, placebo-controlled, double-blinded study at an academic tertiary-care medical center. Interventions were testosterone gel (TRT, n=20) or placebo gel (n=19) for 24 weeks. We included 39 men (50─70 years) with type 2 diabetes (T2D) on metformin monotherapy with bioavailable testosterone levels <7.3 nmol/L. Body composition was assessed by DXA- and MRI-scans; main study outcomes were serum hepcidin-iron, FGF23, phosphate, klotho, and calprotectin. Results: Hepcidin levels decreased during TRT (β=-9.5 ng/mL, P<0.001), lean body mass (β=1.9 kg, P=0.001) increased, and total fat mass (β=-1.3 kg, P=0.009) decreased compared to placebo. Delta hepcidin was not associated with changes in lean body mass or fat mass. Iron and the pathways of FGF23-phosphate-klotho and calprotectin were unchanged during TRT. Conclusions: During TRT, the reduction in hepcidin was not associated with circulating iron levels, lean body mass, or fat mass; these findings suggested a direct anti-inflammatory effect of TRT and no indirect effect mediated through these factors.

In view of the problem that the output thrust of solenoid actuator is affected by various factors and is difficult to calculate in actual working conditions, this paper proposes a semi-analytical model constructed by magnetic field subdomain method with internal and external boundary conditions in cylindrical coordinate system for calculation, and the general solution equations of magnetic vector potential for each subdomain are derived and solved by MATLAB. Taking a push-pull electromagnet as an example, the finite element simulation and experimental comparative analysis are carried out. The correctness and applicable conditions of the subdomain method are illustrated by comparing the gradient plot of magnetic vector potential, inductance curve and electromagnetic force. By calculating the output thrust after considering the core gravity, spring force and electromagnetic force, it is shown that this method has the advantage of computational flexibility compared with the finite element method, and it is easier to write special algorithms according to various working conditions to calculate the important parameters in engineering applications.

In this paper we describe a method which combines sentiment analysis with machine learning techniques and/or multivariate statistical analysis. By applying this methodology it is possible to classify a collection of texts into two or more groups or clusters. On the basis of a number of previously defined clusters, the novelty of the outlined approach is the use of the sentiment analysis results as input to the machine learning model or multivariate statistical analysis. Once the classifier has been obtained, we can assign a given text into one of the pre-established clusters. The groups or clusters can represent different time periods, classes of texts transcribed from different conversations, etc. The method is illustrated through an example taken from one of the two studies in which we have applied this methodology. In one of the studies, the method was used to classify press news of a volcanic eruption, while in the other study it was used to classify the conversations recorded between a chatbot with different kinds of speakers (humans or chatbots). This last study was the seminal work in which we introduced this methodology.

The main purpose of our research is the evaluation of the efficacity of solvent polarity on phenolic composition, as well as the antibacterial, and antioxidant activities of extract of Moroccan Mentha aquatica L., leaves. To attempt these objectives, the HPLC-DAD was used to identify the biomolecules. The total amount of phenolic and flavonoid content was determined using the Folin-Ciocalteu and aluminum trichloride processes as well as the DPPH, RP, and TAC tests were used to evaluate the antioxidant capabilities. In addition, by employing both in vitro and in silico analysis through the microdilution method, the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of the extracts were assessed against multidrug-resistant bacteria. Furthermore, the High-Performance Liquid Chromatography (HPLC) analysis indicated that all extracts of M. aquatica were abundant in noteworthy phytochemical compounds, especially gallic acid, vanillic acid, chlorobenzoic acid, quercetin, and kaempferol. Furthermore, the results indicated that the total phenolic content was higher in hydroethanolic extract (62.19 ± 1.19 mg GAE/g DW) in contrast to the acetonic and aqueous extracts (22.22 ± 0.64, and 22.44± 0.57 mg GAE/g DW) respectively. Similarly, the aqueous ethanol extract contained the greatest flavonoid concentration, with values of 29.15± 0.09 mg QE/g DW when compared with the other extracts. The seam extract poses excellent antioxidant power with an IC50 of 0.06 ± 0.00 mg/mL for the DPPH test, and lower RP with EC50 of 80± 0.00 µg/ml when compared with acetonic and aqueous extract (370± 0.00 and 460± 0.01 µg/mL) respectively. Moreover, the hydroethanolic extract has a high level of TAC 75.09± 2.00 mg EAA/g DW, followed by aqueous extract carrying a value of 28.53 ± 1.36 mg EAA/g DW. The antibacterial capacity is ranged between 0.78 ± 0.05 mg/mL and 12.60 ± 0.00 mg/L. The results of the in-silico study demonstrated that quercetin, vanillic acid, and naringenin components contribute to the antioxidant capability. While gallic acid, kaempferol, and quercetin components are attributed to the antibacterial capacity.

The state of the grinding wheel in the grinding process directly affects the surface quality of the workpiece. The monitoring of the wear state of the grinding wheel can effectively identify the wear information of the grinding wheel and timely and effectively repair the grinding wheel. In this paper, a multi-sensor fusion precision grinding wheel wear intelligent monitoring system is established for typical difficult-to-machine aerospace material titanium alloy, and a multi-eigenvalue fusion algorithm based on improved support vector machine (SVM) is proposed. The extracted sound emission signal wavelet packet decomposition coefficient mean square value, force signal grinding force ratio, and vibration signal effective value are used as the input of the improved support vector machine, and the identification strategy is adjusted by the entropy weight evaluation method. The results show that the monitoring system established in this paper can effectively identify the wear state of the grinding wheel, and the monitoring accuracy can reach more than 92%.

In order to improve the stiffness of the flexible robot,this paper proposes a variable-stiffness elastic actuator to improve the rigidity of flexible robots. The actuator integrates the working principles of a pneumatic drive, wedge structure, and particle blockage. the tensile stiffness of the actuator is nonlinearly negatively correlated with the air pressure because of the structural and material properties.The compressive stiffness and lateral stiffness increases nonlinearly as air pressure increases, being 3and 121 times greater at 0.17 MPa compared to 0 MPa, respectively. Beyond 0.17 MPa, the two stiffness of the actuator experiences incremental growth due to wedge impedance forces.

Objective: We reviewed the available literature on patients undergoing minimally invasive mitral valve surgery (MIMVS) with either transthoracic clamping (TTC) or endoaortic balloon occlusion (EABO). Methods: Original research studies that evaluated the perioperative outcomes of TTC versus EABO group were identified, from 2000 to 2024. The incidence of all-cause mortality, cerebrovascular accidents (CVA), and aortic dissections were the primary endpoints. The cardiopulmonary bypass (CPB), cross-clamp, and ventilation time, along with the incidence of conversion to sternotomy, re-exploration, new-onset atrial fibrillation (AF), postoperative acute kidney injury (AKI), ICU stay, and LOS were the secondary endpoints. Subgroup analyses were performed regarding EABO cannulation approach (femoral and aortic) and MIMVS approach (video-assisted and robotic-assisted). Sensitivity analyses were performed including risk-adjusted populations and with the leave-one-out method. Results: Sixteen studies were included in the qualitative and quantitative synthesis. After pooling data from 6,335 patients, both groups demonstrated similar outcomes on all primary and secondary endpoints in the non-adjusted and adjusted total cohort analyses. These outcomes were further validated by the leave-one-out sensitivity analysis. In addition, the aortic cannulation EABO was associated with lower cross-clamp time, followed by TTC and femoral cannulation EABO approach. Furthermore, in the video-assisted subgroup analysis, the EABO approach was associated with a higher incidence of CVA, conversion to sternotomy, and longer ICU stay compared to the TTC group. Conclusions: The present meta-analysis indicates that both aortic occlusion techniques are safe and feasible in the context of MIMVS. A future well-designed Randomized-Control Trial should further validate the current outcomes.

The systematic sampling is used as a method to get the quantitative results from the tissues and the radiological images. Systematic sampling on real line (R) is a very attractive method within which the biomedical imaging is consulted by the practitioners. For the systematic sampling on R, the measurement function (MF) is occurred by slicing the three-dimensional object equidistant systematically. The currently used covariogram model in variance approximation proposed by [28,29] is tested for the different measurement functions in a class to see the performance on the variance estimation of systematically sampled R. This study is an extension of [17], and an exact calculation method is proposed to calculate the constant λ(q,N) of confidence interval in the systematic sampling. The exact value of constant λ(q,N) is examined for the different measurement functions as well. As a result, it is observed from the simulation that the proposed MF should be used to check the performances of the variance approximation and the constant λ(q,N). Synthetic data can support the results of real data.

Enhancing spectral efficiency, especially in Non-line-of-Sight environments, is emerging as a pivotal necessity when dealing with the evolving landscape of 5G networks and beyond, sur-passing the capabilities of previous 4G systems to achieve a high information rate combined with minimal interference. Contrary to depending on the traditional Orthogonal Multiple Access (OMA) systems to tackle the issues caused by Non-line-of-Sight (NLoS) environments, advanced wireless networks are focusing on adopting innovative models such as Non-Orthogonal Multiple Access (NOMA), MIMO, IRS technology, etc. In this paper, we present technologies that can be integrated with NOMA to enhance communication reliability in environments that suffer from issues such as limited coverage and lower spectral efficiency mainly caused by huge obstacles. Our exploration includes the fundamental concepts of Cooperative NOMA (C-NOMA), Multiple Input Multiple Output (MIMO), Intelligent Reflective Surfaces (IRS), Unmanned Aerial Vehicles (UAVs), and Energy Harvesting (HV), which adds a layer of sophistication, promising not only improved connectivity but also contributing to a more reliable and environmentally friendly data trans-mission landscape.

The development of accurate dynamic battery pack models for electric vehicles (EVs) is critical for the ongoing electrification of the global automotive vehicle fleet, since these serve as a key element in the energy performance of an EV powertrain system. The Equivalent Circuit Model (ECM) technique at the cell level is commonly employed for this purpose, combining accuracy and efficiency in the representation of battery operation within the broader powertrain system. In this study, a second-order ECM model of a battery cell is being developed using Modelica, an equation-based modeling language. Parameter lookup tables at multiple levels of state of charge (SoC), extracted from Li-ion battery cells with 4 different commonly used cathode materials, have been utilized. This approach allows for a representation of the battery systems that are used in a wide range of commercial EV applications. To verify the model, an integrated EV model is developed and simulation results of the FTP75 driving cycle have been compared against an equivalent application in MATLAB Simulink. The findings demonstrate a close match between the results obtained from both software across different system points. Specifically, the maximum deviation of SoC is limited to 0.08% and the maximum value of relative voltage deviation is 1.4%. The verified model enables the exploration of multiple possible architecture configurations of EV powertrains with Modelica.

Keywords: Linear differential arrays; beam steering; frequency-invariant beamforming.

Spontaneous tumours in higher plants can develop depending on plant genotype without any pathogen invasion. Spontaneous tumour formation on the taproots is consistently observed in certain inbred lines of radish (Raphanus sativus var. radicula Pers.). In this work, we have sequenced the genomes of two closely related radish inbred lines that differ in their ability to spontaneously form tumours. We have identified numerous single nucleotide variants (amino acid substitutions, insertions or deletions) that are likely to be associated with the spontaneous tumour formation. Furthermore, we performed the identification of CLE and WOX genes the genomic sequences of the radish inbred lines and, as a result, identified two unique radish CLE genes which probably encode proteins with multiple CLE domains. The results obtained provide a basis for investigating the mechanisms of plant tumour formation and also for future genetic and genomic studies of radish.

The main contribution of this paper is to develop a graphical tool to evaluate the suitability of a candidate parametric model to fit a data set. The practical motivation is to check the adequacy of the so called SAINT model proposed in Jarner and Kryger (2011). This model has been implemented in practice by an important European pension fund concerned with setting annuity reserves for all current or former employees of Denmark. So, one particular relevant question is whether this mortality model is actually fitting old-age. Our graphical test can be described as follows. First we transform the data by means of the parametric model which is being evaluated. Should the model be correct, the transformed data will be in accordance with an Exponential distribution with rate 1. Then we construct a family of local linear hazard estimates based on the data on the transformed scale. Finally we use the statistical tool SiZer to assess the goodness-of-fit of the Exponential distribution to the data on the transformed scale. If the model is correct the SiZer map should not reveal any significant feature in the family of kernel estimates. Our method allow us to establish a diagnostic regarding the validity of the SAINT model when describing mortality patterns in four different countries.

This article presents a buck converter in which the inductor has been replaced by a transmission line. This approach would be practically conceivable if the power supply and load have a greater spatial distance. In the time domain, this new converter can be described by a system of coupled partial and ordinary differential equations. In the frequency domain, a transcendental transfer function is obtained. For comparison with an equivalently parameterized conventional converter, Padé approximants are derived. A linear controller is designed for the converter topology under consideration.

Elizabethkingia anophelis is an opportunistic pathogen causing lifethreatening infections in humans, particularly in immunocompromised patients, neonates and elderly. Infections caused by this species are exceptionally challenging to treat due to its multiresistance to antimicrobials. We report a case of central line-associated bloodstream infection by E. anophelis in a 2.5-year-old girl with acute lymphoblastic leukemia successfully treated with a combination of piperacillin/tazobactam and amikacin. The literature was also reviewed on paediatric infections caused by E. anophelis. Accurate identification with MALDI-TOF, or using molecular techniques, is crucial because of varying susceptibilities among species. Early, accurate diagnosis and prompt effective treatment optimize outcomes.

The time-resolved flowfield of a spatially oscillating jet emitted by a Sweeping Jet (SWJ) actuator is investigated numerically using three-dimensional Reynolds-averaged Navier-Stokes (3D-URANS) equations. Numerical simulations are performed for a practical range of mass flow rates providing flow conditions ranging from incompressible to subsonic compressible flows. A linear relationship between the mass flow rate and the jet oscillation frequency is found. The results of the numerical model are compared with the experimental data in the literature, and good agreement is found. Additionally, it is observed that the SWJ actuator frequency response switches from one linear mode to another linear mode when the compressibility effects become important.

Thermal-based actuators are known for generating large force and displacement strokes at mesoscale (millimeter) regime. In particular, two-phase thermal actuators are found to benefit from the scaling laws of physics at mesoscale to offer large force and displacement strokes; but they have low thermal efficiencies. As an alternative, a combustion-based thermal actuator is proposed and its performance is studied in both open and closed cycle operations. Through a physics-based lumped-parameter model, we investigate the behavior and performance of the actuator using a spring-mass-damper analogy and taking an air standard cycle approach. Three observations are reported: (1) the mesoscale actuator can generate peak forces of up to 400 N and displacement strokes of about 16 cm suitable for practical applications; (2) an increase in heat input to the actuator results in increasing the thermal efficiency of the actuator for both open and closed cycles; and (3) for a specific heat input, both the open and closed cycle operations respond differently \textemdash different stroke lengths, peak pressures, and thermal efficiencies.

Metal-catalyzed lipid oxidation is a major factor in food waste, as it reduces shelf life. Addressing this issue, our study investigates the potential of hydrolysates derived from potato protein, a by-product of potato starch production, as metal chelating antioxidants. Through sequential enzymatic hydrolysis using Alcalase or Trypsin combined with Flavourzyme, we produced various hydrolysates, which were then fractionated via ultrafiltration. Using a combination of peptidomics and bioinformatics, we predicted the presence of metal-chelating and free radical scavenging peptides across all hydrolysate fractions, with a trend indicating a higher content of antioxidant peptides in lower molecular weight fractions. To validate these predictions, we utilized Surface Plasmon Resonance (SPR) and a 9-day emulsion storage experiment. While SPR demonstrated potential in identifying antioxidant activity, it faced challenges in differentiating between hydrolysate fractions due to significant standard errors. In the storage experiment, all hydrolysates showed lipid oxidation inhibition, though not as effectively as EDTA. Remarkably, one fraction (AF13) was not significantly different (p < 0.05) from EDTA in suppressing hexanal formation. These results highlight SPR and peptidomics/bioinformatics as promising yet limited methods for antioxidant screening. Importantly, this study reveals the potential of potato protein hydrolysates as antioxidants in food products, warranting further research.

Recent advancements in semiconductor photonic and electronic devices such as Uni-travelling-carrier photodiodes (UTC-PDs), have played a significant role in the development of Terahertz communication technology. However, a major challenge that still persists is the limited output power from a single UTC-PD required for practical transmission distances. To enhance the output power, we propose and demonstrate a novel Terahertz wave power combining technique using a photomixer device that comprises of two arrayed UTC-PDs monolithically integrated with a microstrip line-based 2 × 1 Wilkinson power combiner and a rectangular patch antenna on a Silicon Carbide (SiC) substrate at 300 GHz. At photocurrents of 8 mA and 10 mA from the two UTC-PDs, the device experimentally exhibited a 7.3 dB increase in power relative to the power obtained with 8 mA UTC-PD and a 4.4 dB increase in power relative to the power obtained with 10 mA UTC-PD, when both UTC-PDs were irradiated. This implies that power can be enhanced by a factor of N2 if the photocurrent is multiplied by a factor of N. This technology presents a holistic and cutting edge platform for further power multiplication by further increasing the number of arrayed UTC-PDs.

Previous control methods developed by our research team cannot satisfy the high-accuracy requirements of unmanned surface vessel (USV) path-tracking during bathymetric mapping because of the excessive overshoot and slow convergence speed. For this reason, this study developed an adaptive fuzzy integral-derivative line-of-sight (AFIDLOS) guidance law for USV path-tracking control. Integral and derivative terms were added to counteract the effect of the sideslip angle, with which the USV could be quickly guided to converge to the planned path for bathymetric mapping. To obtain a high-accuracy of the look-ahead distance, a fuzzy control method was proposed. The proposed method was verified using simulations and outdoor experiments. The results demonstrate that the AFIDLOS guidance law can reduce the overshoot by 79.85%, shorten the settling time by 55.32% in simulation experiments, and reduce the average cross-track error by 10.91%, and can ensure a 30% overlap of neighboring strips of bathymetric LiDAR outdoor mapping when compared with the traditional method.

This paper employs the Finite Element Method (FEM) to simulate and analyze the effects of corrosion defect parameters on the stress and failure pressure of pipelines. It investigates how the boundary conditions of the pipeline model influence stress and examines the sensitivity of failure pressure to corrosion defect parameters. A nonlinear regression equation has been developed from a dataset obtained through simulation experiments to predict the failure pressure of corroded pipelines. To validate the effects of corrosion defect parameters on failure pressure, a hydrostatic test platform for an API 5L X65 pipeline with corrosion defects was established to measure stress levels and failure pressures across varying corrosion defects. The study reveals that failure pressure is negatively correlated with corrosion length and depth, while positively correlated with corrosion width. Among these parameters, corrosion depth exerts a more significant influence on the pipeline's failure pressure than corrosion length and width. Within the range of corrosion defect parameters examined, the maximum deviation of the prediction equation's results from the simulation results is 8.71%, with an average deviation of 5.81%. The standard deviation of the fitted residuals is 0.01837. Additionally, the maximum deviation between the predicted results and experimental measurements is 8.39%, with an average deviation of 7.77%. The strong agreement between the predicted results from the equation and the actual measured data underscores the effectiveness of the nonlinear regression equation.

For multi-sensor integrated systems, such as a mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, though the latter is more reliable.

As the most important component of soft robot, the pneumatic actuator can drive robot movement. However, the effect of the actuator pneumatic network geometry on the actuator load capacity is insufficient. In this paper, the finite element analysis method is applied to calculate the load force and stability torque of the pneumatic actuator under a wide range of length and height dimensions of the pneumatic network. The effect of the network size on the structure rigidity, load capacity and deformation of the actuator is analyzed. Based on the calculation results, the effect of network structure size on the deformation and load capacity is analyzed, and the optimal geometric results with the maximum load capacity are obtained. This study provides theoretical guidance for the structural design and optimization of the pneumatic actuator.

Conducting related research is crucial since there are still many problems that need to be resolved in the research on soft robots in the areas of material selection, structure design and manufacture, and drive control. Soft manipulators, a subset of soft robots, are now a popular area of study for many researchers. In comparison to typical manipulators, soft manipulators feature a high degree of gripping flexibility and a basic morphological structure. They are composed of flexible materials. It has a wide range of potential applications in healthcare, rehabilitation, bionics, and detection, and it can compensate for the drawbacks of rigid manipulators in some use scenarios. A modular soft-body torsional gripping system is developed after a torsional and gripping actuator is conceived, constructed, and its performance is examined. The torsion actuator and the grasping actuator can be combined in the system in a modular fashion. With the help of RGB-D vision algorithms, this multi-modular setup makes it possible to combine soft actuators with various twisting degrees and achieve exact gripping. Through pneumatic control, the target object is precisely grasped and rotated at various angles, enabling rotation of the target object in three dimensions.

Impact characterization of linear resonant actuator (LRA) is studied experimentally by newly developed drop tester, which can control various experimental uncertainty such as rotational moment, air resistance, secondary impact and so on. The feasibility of this test apparatus was verified by comparison with free fall test. By utilizing a high-speed camera and measuring the vibrational displacement of spring material, the impact behavior was captured and the damping ratio of the system was defined. Based on the above processes, the finite element model was established and the experimental and analytical results were successfully correlated. Finally, the damage of the system from impact loading can be expected by developed model and as a result, this research can improve the impact reliability of LRA.

This paper proposes a definition of fractional line integral, generalising the concept of fractional definite integral. The proposal replicates the properties of the classic definite integral, namely the fundamental theorem of integral calculus. It is based on the concept of fractional anti-derivative used to generalise the Barrow formula. To define the fractional line integrals the Gr\"unwald-Letnikov and Liouville directional derivatives are introduced and their properties described. The integral is defined first for broken line paths and afterwards to any regular curve

The paper presents the possibility of using KINECT v2 module to control an industrial robot by means of gestures and voice commands. It describes elements of creating software for off-line and on-line robot control. The application for KINECT module was developed in C# language in Visual Studio environment, while the industrial robot control program was developed in RAPID language in RobotStudio environment. The development of a two-threaded application in RAPID language allowed to separate two independent tasks for the IRB120 robot. The main task of the robot is performed in thread no. 1 (responsible for movement). Simultaneously working thread no. 2 ensures continuous communication with the KINECT system and provides information about the gesture and voice commands in real time without any interference in thread no. 1. The applied solution allows the robot to work in industrial conditions without negative impact of communication task on the time of robot’s work cycles. Thanks to the development of a digital twin of the real robot station, tests of proper application functioning in off-line mode (without using a real robot) were conducted. Obtained results were verified online (on the real test station). Tests of correctness of gesture recognition were carried out, the robot recognized all programmed gestures. Another test carried out was the recognition and execution of voice commands. A difference in the time of task completion between the actual and virtual station was noticed - the average difference was 0.67 s. The last test carried out was to examine the impact of interference on the recognition of voice commands. With a 10dB difference between the command and noise, the recognition of voice commands was equal to 91.43%. The developed computer programs have a modular structure, which enables easy adaptation to process requirements.

Biomimetic materials are substances that replicate natural structures. There are several methods for producing such materials with highly developed surfaces from a wide range of polymers, but electrospinning is of particular interest due to its simplicity of implementation and the ability to modify the produced fibrous materials resembling structures found in living organisms. This study explores new biomimetic materials based on polyhydroxyalkanoates, specifically poly-3-hydroxybutyrate, modified with chlorophyll derivatives. The research investigates the impact of chlorophyll derivatives on the morphology, supramolecular structure, and key properties of nonwoven materials. The obtained results are of interest for the development of new biomimetic environmentally friendly materials for biomedicine with special properties.

Systematic reviews represent a powerful instrument to summarize the existing evidence in medical literature. However, articles for a systematic review are hard to identify, and mostly require a structured search of the literature through a number of databases, using keyword-based search strategies, followed by the painstaking manual selection of pieces of evidence that are pertinent to the query. A.I. algorithms may offer solutions to reduce the workload on investigators. We applied BERTopic, a newer and much-recognized transformer-based topic-modeling algorithm, to two datasets of 6137 and 5309 articles of newly published systematic reviews in the area of peri-implantitis and bone regeneration in implant dentistry. In the two datasets, BERTopic identified 14 and 22 clusters, respectively, and it automatically created labels describing the nature of the topics for each individual cluster based on semantic interpretation of their titles. Most themes regarded the query theme, but in both conditions, BERTopic also uncovered articles related to off-themes, which composed around 30% of the dataset—with sensitivity up to 0.79 and specificities of at least 0.99. Our results suggest that adding a topic-modeling step to the screening process could potentially save working hours for researchers involved in systematic reviews of the literature.

The quest for youthful, healthy skin and full, vibrant hair has long been a driving force in the dermocosmetics field. However, traditional approaches often struggle to address the underlying causes of aging, damage, and hair loss. Regenerative cosmetics, powered by skin tissue engineering, offer a transformative alternative. This review explores the emerging field of using engineered skin tissues for cosmetic purposes, focusing specifically on their potential for anti-aging, repair, and hair restoration applications. We discuss how these technologies aim to rejuvenate aging skin by promoting collagen production, reducing wrinkles, and improving overall skin function. Additionally, the use of engineered skin for wound healing and scar reduction is examined, highlighting their potential to improve the appearance and functionality of damaged skin. Finally, we advance the exciting prospects of utilizing skin tissue engineering techniques to regenerate hair follicles, potentially offering solutions for hair loss and promoting denser hair growth.

This study systematically addresses the challenge of accurately modeling memristors, focusing on four distinct types doped with tungsten, tin, chromium, and carbon, fabricated by Known Inc. A comprehensive characterization was performed by subjecting the devices to sinusoidal excitations with varying frequencies and amplitudes, followed by data averaging and high-frequency filtering. The resulting measurements were fitted using three prominent memristor models: VTEAM, MMS, and Yakopcic, with additional bespoke modifications assessed. These models, typically formulated as coupled algebraic-differential equations integrating electrical quantities (voltage and current) with internal state variables governing device dynamics, were optimized using two robust approaches: (1) interior-point optimization with gradient-based search, and (2) Nelder-Mead gradient-free optimization, both with box constraints applied. A thorough comparison and discussion of the optimized model parameters ensued, accompanied by an examination of sensitivity to diverse frequency and amplitude ranges. The findings inform conclusions and provide a foundation for future refinements, underscoring the importance of multi-model evaluation and advanced optimization strategies in precise memristor modeling. The presented methodology offers a valuable framework for elucidating optimal modeling paradigms tailored to specific memristor architectures and operating regimes, ultimately enhancing their integration in emerging neuromorphic and computational applications.

It’s very well known that the world's attention is currently focused on the energy transition. The energy security, in addition to the drive to reduce greenhouse gas emissions in order to limit global warming, and the generalization of the access to energy, have contributed to adoption of the Moroccan Energy Strategy with a strong focus on Renewable Energies (RE). Morocco is notoriously poor in conventional fossil primary energy resources with an energy dependence on the order of 90%. The energy crisis and that resulted from Covid-19 pandemic and the geopolitical conflicts, combined compounded with steady increase in demand have heavily affected the security and the stability of the country's energy situation. The transition to RE, by strongly engaging in the implementation of several solar, wind and hydro energy projects benefiting from the country's excellent solar and wind energy potential, has made the country the leader in RE in Africa. By 2030, the share of RE in the installed capacity is expected to reach 52%. In this work, an overview of the current situation of RE (particularly solar energy) in Morocco is provided, including, the potentials, obstacles and challenges, and future perspectives. Thanks to its high solar potential location, it’s predictable that Morocco effort will be focused on this field: the Erasmus Plus Innomed Project is a virtuous example of international cooperation, aiming at create a Solar Energy Network, in synergy with EU Partners.

Underwater natural gas pipelines constitute critical infrastructure for energy transportation. Any damage or leakage in these pipelines poses serious security risks, directly threatening marine and lake ecosystems and potentially causing operational issues and economic losses in the energy supply chain. Due to the difficulty in detecting deterioration over time and regularly inspecting these submerged pipelines by divers, the use of unmanned underwater vehicles (UUVs) becomes crucial in this field. In this study, an underwater pipeline tracking experiment was carried out by providing autonomous features to a remote-controlled unmanned underwater vehicle. During the tracking of the underwater pipeline, damages were identified, and the locations of these damages were determined. The navigation information of the underwater vehicle, including orientation in the x, y, z axes (roll, pitch, yaw) from a gyroscope integrated with magnetic compass, speed and position information in the three axes from an accelerometer, and the distance to the water surface from a pressure sensor, was integrated into the vehicle. Pre-tests determined the necessary pulse width modulation values for the thrusters of the vehicle, enabling autonomous operation by providing these values as input to the thruster motors. In this study, the vehicle moves in 3D was achived by the vertical thruster of the vehicle was activated to maintain a specific depth, and applying equal force to the vehicle’s right and left thrusters forward movement, while differential force induced deviation angles. In pool experiments, the unmanned underwater vehicle autonomously tracked the pipeline as intended, identifying damages on the pipeline using images captured by the vehicle's camera. The images for damage assessment were processed using a convolution neural network (CNN) algorithm, which is a deep learning method. The position of the damage relative to the vehicle was estimated from the pixel dimensions of the identified damage. The location of the damage relative to its starting point was obtained by combining these two positional pieces of information from the vehicle's navigation system. The all study was performed within the Python environment.

This paper addresses a mode-dependent state-feedback H∞ control for descriptor hybrid systems, considering both the absence and presence of actuator saturation. Firstly, the necessary and sufficient conditions for the stochastic admissibility criterion with H∞ performance ? of the closed-loop system is proposed. Given the proposed non-convex condition, the author reformulates it into linear matrix inequalities (LMIs). Then, to extend the result to the systems with actuator saturation, the actuator saturated control input is expressed as a linear combination of given state-feedback control input and a virtual control input that remains under the saturation level. To verify this expression, the set invariant condition is also suggested by using the singular mode-dependent Lyapunov function candidate. Therefore, the LMI conditions for the existence of the mode-dependent state-feedback H∞ control and the ellipsoidal shape of invariant set are successfully derived. Two numerical examples demonstrate the effectiveness of the proposed approach in optimizing H∞ performance $\gamma$ and identifying the largest invariant set.

Shape Memory Polymer (SMP) actuators are smart materials that adapt and switch shape in response to environmental conditions, allowing controlled and dynamic building systems. The integrated SMP strip enabled the adaptive facade shading system to operate independently and with flexibility under certain thermoresponsive conditions to regulate building performance. This study aims to improve adaptive façade performance in a hot-humid climate by determining optimal thermal activation factors for the shape memory polymer. This was achieved by comprehensively examining and analysing the impact of various SMP activation parameters on energy efficiency, thermal comfort, and visual comfort. In addition, dynamic IES-VE building energy simulation was used to evaluate the thermal performance of the adaptable facade. The results were validated using a multicriteria approach to compare with the existing glass façade of a high-rise apartment. The results showed that the coactivation technique, which combines solar radiation and air temperature triggers, proved to be the most efficient strategy to improve the performance of the adaptive façade. This strategy minimised heat gain, lowered indoor temperatures, reduced glare, and enhanced daylight comfort, resulting in notable energy savings through reduced cooling consumption. The study concluded that the utilisation of SMP actuators with fine-tuning activation parameters significantly optimised adaptive façade performance, promoting functionality, efficiency, and sustainability in buildings.

Based on the need for real-time sag monitoring of Overhead Power Lines (OPL) for electricity transmission, this article presents the implementation of a hardware and software system for online monitoring of OPL cables and cable sag determination. The mathematical model based on differential equations and the methods of algorithmic calculation of OPL cable sag are presented. Considering that, based on the mathematical model presented, the calculation of OPL cable sag can be done in different ways depending on the sensors used, and the presented application uses a variety of sensors. Therefore, a direct calculation is made using one of the different methods. Subsequently, the verification relations are highlighted directly and, respectively, the calculation by the alternative method, which uses another group of sensors, to generate both a verification of the calculation and the functionality of the sensors, thus obtaining a defect observer of the sensors. The hardware architecture of the OPL cable online monitoring application is presented, together with the main characteristics of the sensors and communication equipment used. The configurations required to transmit data using the ModBUS and ZigBee protocols are also presented. The main software modules of the OPL cable condition monitoring application are described, which ensure the monitoring of the main parameters of the power line and the visualisation of the results both on the electricity provider's intranet using a web server and MySQL database, and on the Internet using an Internet of Things (IoT) server. This categorisation of the data visualisation mode is done in such a way as to ensure a high level of cyber security. Starting from the mathematical model of the OPL cable sag calculation, it goes through the stages of creating such a monitoring system, from the numerical simulations carried out using Matlab to the real-time implementation of this monitoring application. The main modules of the application software are: the software module for reading quantities from the sensor network through a ModBUS Input/Output (I/O) server, the software module for real-time calculation of the OPL cable sag, the software module for read/write operations based on MySQL type data, the software module for transferring data to the user's intranet through a web server, and the software module for viewing data by authorised users based on user and password through an IoT server. The development software environments used are Matlab and Laboratory Virtual Instrument Engineering Workbench (LabVIEW).

Among the various types of gas sensors, the chemoresistive gas sensors based on metal oxides are considered the most attractive ones due to their simple operation, low costs and miniaturization. Thin films of V2O5 undoped and doped with TiO2 were studied as nitrogen dioxide, methane and hydrogen sensors. The experimental kinetics of the electrical conductivity changes due to introduction and removal of gas on metal oxide gas sensors were successfully explained in terms of the Langmuir adsorption theory.

Nonlinear nonparametric statistics (NNS) algorithm offers new tools for curve fitting. A relationship between k-means clustering and NNS regression points is explored with graphics showing a perfect fit in the limit. The goal of this paper is to demonstrate NNS as a form of unsupervised learning, and supply a proof of its limit condition. The procedural similarity NNS shares with vector quantization is also documented, along with identical outputs for NNS and a k nearest neighbours classification algorithm under a specific NNS setting. Fisher's iris data and artificial data are used. Even though a perfect fit should obviously be reserved for instances of high signal to noise ratios, NNS permits greater flexibility by offering a large spectrum of possible fits from linear to perfect.

The research on the excavation mechanical properties of underpass tunnels has already had certain results, but fewer of them consider the effects of dynamic and static loads on the excavation mechanical properties of underground tunnels at the same time, especially the lack of research cases of double-line highway tunnels with angled underpasses of existing railway tunnels. In this paper, based on the tunnel project of the new double-line Shiqian Highway Tunnel passing under the Hurong Railway at an oblique angle, the mechanical parameters of the rock body in the cross-tunneling area under the influence of static and dynamic load coupling are obtained by using the disturbance quantification coefficients and the Hoek-Brown criterion based on the method of over-advanced geological prediction and the investigation of the surrounding rock on the palisade face, and the engineering-scale finite element model is constructed and the mechanical characteristics of the excavation in the tunnel of the double-lane highway tunnel passing under the existing railroad under the influence of the static and dynamic loads are analyzed. The results show that: the new tunnel rock movement law for the top of the arch sinking, bottom plate bulging, side wall to move outward, the height and width of the arch and bottom plate arch with the tunnel excavation and increase, the side wall rock displacement effect is smaller; left and right lines of the tunnel disturbed area of the rule of change is similar; the existing tunnel bottom plate displacement is more than the top plate and the left and right side walls by the excavation of the time step influence is larger. Typical profile displacement is mainly determined by the distance from the excavation surface; the new tunnel in the four types of calculation conditions of the rock disturbance angle is the same; the existing tunnel roof and side wall Von Mises stress extreme occurs in the tunnel structure, the bottom plate there are pressure relief and pressure-bearing areas; based on the displacement control criteria, the recommended upper and lower step blasting method.

Due to its potential harm to space payload, microwave corona breakdown of microstrip circuits has attracted much attention. This work describes an efficient way to suppress corona breakdown. Since corona breakdown threshold is determined by the highest electric field intensity at the surface of microstrip circuits, lacquer coating with thickness of tens of microns is sprayed on the top of microstrip circuits. The applied dielectric coating is used to move the discharge location away from circuit’s surface which is equivalent to reduce the highest electric field intensity on the in-terface of solid/air of the circuit and thus results into higher breakdown threshold. Two designs of classic coupled-line band-pass filter were used for verification. Corona experimental results at 2.5 GHz show that, in the interested low pressure range (100 to 4500 Pa), 5.3 dB improvement of mi-crowave corona breakdown threshold can be achieved for a filter with narrowest gap of 0.2 mm while its electrical performances like insertion loss, Q-factor are still acceptable. A threshold improvement prediction method is also presented and validated.

The manuscript deals with a new two-parameter unit stochastic distribution, obtained by transforming the Gumbel distribution, using generalized logistic mapping, into a unit interval. The distribution thus obtained is called the Gumbel–Logistic Unit (abbr. GLU) distribution, and its key stochastic properties have been investigated in detail. Among others, it is shown that the GLU distribution, unlike the Gumbel one which is always positively asymmetric, can take both asymmetric forms. Also, the procedure for estimating parameters based on quantiles, along with the asymptotic properties of the obtained estimators and the study of their numerical simulation, is presented. Finally, the application of the GLU distribution in modeling some real–world data related to telecommunications is considered.

Our objective was to investigate the effects of topically applied neuropeptide Y (NPY) on ischemic wounds. Initially, the animal model for ischemic wound healing was validated using 16 male Sprague-Dawley albino rats. In the intervention study, an additional 28 rats were divided into three groups: NPY (0.025%), the positive control insulin-like growth factor-I (IGF-I, 0.0025%), and the hydrogel carrier alone (control). The hydrogel was selected due to its capacity to prolong NPY release (p &lt; 0.001), as demonstrated in a Franz diffusion cell. In the animals, an 8-mm full-thickness wound was made in a pedunculated dorsal ischemic skin flap. Wounds were then treated and assessed for 14 days, and procured at the end of the experiment for in situ hybridization analysis (RNAscope®) targeting NPY receptor Y2R and for meticulous histologic examination. Wound healing rates, i.e. the percentage wound area changes, did not show an increase with NPY (p = 0.938) but did with rhIGF-I (p = 0.039) compared to the control. Y2R mRNA was not detected in the wounds or adjacent skin but was identified in the rat brain (positive control). Light microscopic examination revealed trends of increased angiogenesis and enhanced inflammatory cell infiltration with NPY compared to control. An interesting secondary discovery was the presence of melanophages in the wounds. Our findings suggest the potential of NPY to enhance neovascularization under ischemic wound healing conditions, but further optimization of the carrier and dosage is necessary. The mechanism is elusive but likely involves NPY receptor subtypes other than Y2R.

Accurate forecasting of icing thickness has a great significance for ensuring the security and stability of power grid. In order to improve the forecasting accuracy, this paper proposes an icing forecasting system based on fireworks algorithm and weighted least square support vector machine (W-LSSVM). The method of fireworks algorithm is employed to select the proper input features with the purpose of eliminating the redundant influence. In addition, the aim of W-LSSVM model is to train and test the historical data-set with the selected features. The capability of this proposed icing forecasting model and framework is tested through the simulation experiments using real-world icing data from monitoring center of key laboratory of anti-ice disaster, Hunan, South China. The results show that the proposed W-LSSVM-FA method has a higher prediction accuracy and it may be a promising alternative for icing thickness forecasting.

Satellites are subject to various severe vibration during different phases of flight. The concept of satellite smart adapter is proposed in this study to achieve active vibration control of launch vehicle on satellite. The satellite smart adapter has 18 active struts in which the middle section of each strut is made of piezoelectric stack actuator. Comprehensive conceptual design of the satellite smart adapter is presented to indicate the design parameters, requirements and philosophy applied which are based on the reliability and durability criterions to ensure successful functionality of the proposed system. The coupled electromechanical virtual work equation for the piezoelectric stack actuator in each active strut is drived by applying D'Alembert's principle. Modal analysis is performed to characterize the inherent properties of the smart adapter and extraction of a mathematical model of the system. Active vibration control analysis was conducted using fuzzy logic control with triangular membership functions and acceleration feedback. The control results conclude that the proposed satellite smart adapter configuration which benefits from piezoelectric stack actuator as elements of its 18 active struts has high strength and shows excellent robustness and effectiveness in vibration suppression of launch vehicle on satellite.

Many spectroscopic diagnostics are routinely used as a technique to infer the plasma parameters from line emission spectra but their accuracy depends on the numerical model or code used for the fitting process. However, the validation of a line shape code requires some steps : comparison of the line shape code with other similar codes for some academic (simple) cases and then more complex ones, comparison of the fitting parameters obtained from the best fit of the experimental spectra with those obtained with other diagnostic techniques and/or comparison of the fitting parameters obtained by different codes to fit the same experimental data. Here we compare the profiles of the hydrogen Balmer β line in a helium plasma computed by six codes for a selected set of plasma parameters and we report on the plasma parameters inferred by each of them from the fitting to a number of experimental spectra measured in a helium corona discharge where the pressure was in the range 1- 5 bar.

The problems of modeling the human bladder and its stress-strain state under external static influence were considered. A method for identification of the anisotropic biomechanical characteristics of bladder tissue was proposed. A FEM model was created, which accepts into regard that the bladder is surrounded by fiber and affected by surrounding organs, and partially protected by pelvic bones. The model considered the presence of constant hydrostatic pressure on the walls of the bladder when it is full. It has been shown that isotropic mechanical characteristics of biological tissue can be used for studying the deformed state of a filled bladder if the filled bladder 300 ml is considered as initial non-deformed stage. This was shown by modeling and verification the effect of the external static force on the bladder. Numerical experiments were conducted based on the constructed model. To validate the results obtained, a series of natural experiments on the effect of external pressure on the bladder under ultrasound control was conducted. In the future, it is planned to use the constructed model to study rupture deformations of the bladder under the influence of static and dynamic loads.

Sports video analysis is an interesting and emerging field in the domain of computer vision. It has become a very popular subject among scholars all over the world in the last decade due to the need of automated classification of events such as offsides, in/out situations, goals and so on. The most important problem in sports video analysis is detection and tracking of ball and players. Extraction of court lines is also another important problem since it is necessary in the classification of aforementioned events. In this study, considering some of the previous work on the subject, we develop a method for tracking the ball and players in tennis videos where the camera position and orientation is supposed fixed.

We revisit a 2023 JAMA-published analysis of data from patients admitted for either COVID-19 or influenza to U.S. Veterans Administration (VA) hospitals in the fall/winter of 2022-2023. We note that baseline characteristics between the cohorts were similar, and the difference in vaccination rates was minimal, even after propensity score weighting. Had the vaccines been even minimally effective, significant differences in vaccination percentages would be expected. These findings call into question any efficacy claims associated with either the COVID-19 or influenza vaccines. Furthermore, the lack of efficacy of the influenza vaccines in reducing hospitalization is consistent with an earlier detailed study that found the same lack of efficacy, further validating the current result. This suggests that comparing vaccination rates between those hospitalized for different vaccine-preventable diseases can serve as a practical method for validating the vaccine efficacy claims of different vaccines.

Many people in the USA have lost their lives or become addicted to opioids via prescription opioids given for chronic pain. The chronic pain epidemic has emerged due to a convergence of factors, including the medicalization of pain as well as injuries happening in the workplace, in the home, or during recreation. Opioid prescriptions rose precipitously from the late 1990’s through to approximately 2020, and despite public awareness, still are increasing. This review examines literature on integrative approaches to chronic pain as delineated by pain type. The review is organized by the most common causes of chronic pain, and randomized controlled trials, meta-analyses and systematic reviews are extracted for each cause of chronic pain. Several promising interventions may alleviate chronic pain of some causes, and some interventions may work across pain causes. Lowering inflammation through dietary or lifestyle regimens may be a general way of reducing pain. Pain can be alleviated through several adjunctive and integrative treatment approaches, which may serve to lower the need for opioid medication.

A constant effort is made in the physical metallurgy of transformation induced plasticity (TRIP) steels. These are multiphase steels, whose mechanical behavior depends on the different phases present, the intrinsic strength of each phase, the work hardening of each constituent and the austenite to martensite transformation, among others. Hard and soft phases can be distinguished in these steels and both stress and strain are distributed between them. The objective of this work was to simulate the stress-strain behavior for two TRIP steels. Bouquerel’s model was modified to account for the initial martensite, a moderate hard austenite and adjustable strain hardening parameters. The austenite fraction that transforms into martensite was computed through an Olson and Cohen model. The Mecking-Kocks model was used to evaluate the increment in the dislocation density and the Rodriguez-Gutierrez model, to compute the hardening of martensite. Ferrite is considered a soft phase, martensite and bainite, hard phases and austenite, a phase with a moderate hardness. The routine was implemented in MATLAB, and results were compared with those obtained experimentally in a tension test of two TRIP steels of the same composition but different heat treatments, obtaining in both cases a good agreement for the stress-strain-curves.

This study analyses regional development in one of the poorest provinces in China, Guizhou Province, between 2000 and 2012 using a multiscale and multi-mechanism framework. In general, regional inequality has been declining since 2000. In addition, economic development in Guizhou Province presented spatial agglomeration and club convergence, which shows how the development pattern of one core area, two-wing areas and a contiguous area at the edge of the province have been developed between 2006 and 2012. Multilevel regression analysis revealed that industrialization and investment level were the primary driving forces of regional economic disparity in Guizhou Province. The influences of marketization and decentralization on regional economic disparity were relatively weak. Investment level reinforced regional economic disparity and the development of core-periphery structure in the province. However, investment level actually weakened the regional economic disparity in Guizhou Province when the variable of time was considered. In addition, both the topography and urban–rural differentiation were the two main reasons for forming a core-periphery structure in Guizhou Province.

We develop an action principle for producing a single fluid, two-constituent system with dissipation in general relativity. The two constituents in the model are particles and entropy. The particle flux creation rate is taken to be zero, while the entropy creation rate is non-zero. Building on previous work, it is demonstrated that a new term (the proper time derivative of the matter space ``metric'') is required in the Lagrangian in order to produce terms typically associated with bulk and shear viscosity. Equations of motion, entropy creation rate, and energy-momentum-stress tensor are derived. Using an Onsager approach of identifying thermodynamic ``forces'' and ``fluxes'' a model is produced which delivers the same entropy creation rate as the standard, relativistic Navier-Stokes equations. This result is then contrasted with a model generated in the spirit of the action principle, which takes as its starting point a specific Lagrangian and then produces the equations of motion, entropy creation rate, and energy-momentum-stress tensor. Unlike the equations derived from Onsager reasoning, where the analogs of the bulk and shear viscosity coefficients are prescribed ``externally'', we find that the form of the coefficients in the second example are a direct result of the specified Lagrangian. Furthermore, the coefficients are shown to satisfy evolution equations along the fluid worldline; also a product of the specific Lagrangian.

This work presents a novel approach for the study of the movement of droplets on inclined surfaces under the influence of gravity and chemical heterogeneities. The developed numerical methodology uses data-driven modeling to extend the applicability limits of an analytically derived reduced-order model for the contact line velocity. More specifically, while the reduced-order model is able to capture the effects of the chemical heterogeneities to a satisfactory degree, it does not account for gravity. To alleviate this shortcoming, datasets generated from direct numerical simulations are used to train a data-driven model for the contact line velocity, which is based on the Fourier neural operator and corrects the reduced-order model predictions to match the reference solutions. This hybrid surrogate model, which comprises of both analytical and data-driven components, is then integrated in time to simulate the droplet movement, offering a speedup of five orders of magnitude compared to direct numerical simulations. The performance of this hybrid model is quantified and assessed in different wetting scenarios, by considering various inclination angles and values for the Bond number, demonstrating the accuracy of the predictions as long as the adopted parameters lie within the ranges considered in the training dataset.

A thorough analysis and comparison of the fatty acid profiles of stipe and blade from Laminaria hyperborea, a kelp species found in the northern Atlantic, is presented. Lipids were extracted and fractionated into neutral lipids, free fatty acids and polar lipids, then derivatized to fatty acid methyl esters prior to GC-MS analysis. A total of 42 fatty acids were identified and quantified, including the n-3 fatty acids α-linolenic acid, stearidonic acid and eicosapentaenoic acid. An n-6/n-3 ratio of 0.8:1 was found in blade and 3.5:1 in stipe, respectively. The ratios vary between the lipid fractions within stipe and blade, with the lowest ratio in the polar lipid fraction of blade. The fatty acid amounts are higher in blade than in stipe, and the highest amounts of n-3 fatty acids are found within the neutral lipid fractions. The amounts of polyunsaturated fatty acids are 3.4 times higher in blade than stipe. This study highlights the compositional differences between the lipid fractions of stipe and blade from L. hyperborea. The amount of polyunsaturated fatty acids, compared to saturated- and monounsaturated fatty acids, as well as the n-6/n-3-ratio, is known to influence human health. In the pharmaceutical, food, and feed industries this can be of importance for production and sale of different health products. Additionally, lipids are today among the unused by products of alginate production, exploiting this material for commercial interest should give both economical and environmental benefits.

This work presents the results of the experimental and theoretical study of the static pull-in of tilting actuation executed by a hybrid levitation micro-actuator (HLMA) based on the combination of inductive levitation and electrostatic actuation. A semi-analytical model to study such the pull-in phenomenon is developed, for the first time, as a result of using the qualitative technique based on the Lagrangian approach to analyze inductive contactless suspensions presented in work and a recent progress in the calculation of mutual inductance and force between two circular filaments. The obtained non-linear model, accounting for two degrees of freedom of the actuator, allows us to predict accurately the static pull-in displacement and voltage. The results of modelling were verified experimentally and agree well with measurements.

Soil and Water Assessment Tool (SWAT) was used to simulate five glacierized river basins that are global in coverage and vary in climate. The river basins included the Narayani (Nepal), Vakhsh (Central Asia), Rhone (Switzerland), Mendoza (Central Andes, Argentina), and Central Dry Andes (Chile) with a total area of 85,000 km2. A modified SWAT snow algorithm was applied in order to consider spatial variation of associated snow melt /accumulation by elevation band across each subbasin. In the previous studies, melt rates varied as a function of elevation resulting from an air temperature gradient while the snow parameters were constant throughout the entire basin. A major improvement of the new snow algorithm is separating the glaciers from seasonal snow based on their characteristics. Two SWAT snow algorithms were evaluated in simulation of monthly runoff from glaciered watershed: 1) the snow parameters are lumped (i.e. constant throughout the entire basin) and 2) the snow parameters are spatially variable based on elevation band-subbasin (i.e. modified snow algorithm). Applying the distributed SWAT snow algorithm improved the model performance in simulation of monthly runoff with snow-glacial regime, so that mean RSR decreased to 0.49 from 0.55 and NSE increased to 0.75 from 0.69. Improvement of model performance was negligible in simulation of monthly runoff from the basins with monsoon runoff regime.

A novel quasi-twisted miniaturized wideband Branch Line Coupler (BLC) is proposed. The design is based on bisecting the conventional microstrip line BLC transversely and folding bisected sections on double-layered substrates with a common ground plane in between. The pair of quarter wavelength horizontal parallel arms is converted to a Z-shape meandered microstrip line in the designed structure. On the other hand, the pair of quarter wavelength vertical arms are cut by half into two lines and converted to a periodically loaded slow wave structure. The bisected parts of BLC are placed on the opposite side of the doubled-layer substrate and connected through four vias passing through the common ground plane. This technique enabled a compact BLC size of 6.4×18 mm2, which corresponds to a surface area miniaturization by ~50% as compared to the classical BLC size of 10×23 mm2 at 6GHz, Moreover, the attained relative bandwidth is 73.9% (4.6-10 GHz) for S11, and 75.8% (4.5-10 GHz) for S33 as compared to 41% for the ordinary BLC at the same resonant frequency. The circuit is constructed on a double-layered low-cost FR4 substrate with a relative permittivity of 4.3, and a loss tangent of 0.025. An isolation of -13dB was realized in both S13 and S31 demonstrating an excellent performance. The transmission coefficients between input/output ports S21, S41, S23, and S43 are between -3.1dB to -3.5dB at the frequency of 6GHz. Finally, the proposed BLC provides phase differences between output ports of 90.5o and 94.8o at the frequency of 6GHz when the input ports 1 and 3 are excited, respectively. The presented design offers the potential of being utilized as a unit cell for building a Butler-matrix (BM) for sub-6GHz 5G beamforming networks.

The development of computational acoustics allows simulation of sound generation and propagation in complex environment. In particular, meshfree methods are widely used to solve acoustics problems through arbitrarily distributed field points and approximation smoothness flexibility. As a Lagrangian meshfree method, smoothed particle hydrodynamics (SPH) method reduce the difficulty in solving problems with deformable boundaries, complex topologies, or multiphase medium. The traditional SPH method has been applied in acoustic simulation. This study presents the corrective smoothed particle method (CSPM), which is a combination of SPH kernel estimate and Taylor series expansion. The CSPM is introduced as a Lagrangian approach to improve accuracy in solving acoustic wave equations in the time domain. Moreover, a boundary treatment technique based on the hybrid meshfree and finite difference time domain (FDTD) method is proposed to represent different acoustic boundaries with particles. To model sound propagation in pipes with different boundaries, soft, rigid, and absorbing boundary conditions are built with this technique. Numerical results show that the CSPM algorithm is consistent and demonstrates convergence with exact solutions. Main computational parameters are discussed, and different boundary conditions are validated to be effective for benchmark problems in computational acoustics.

Endoscopy has made a significant and noteworthy contribution to the field of medical science and technology. Nevertheless, its potential remains constrained due to the limited availability of rigid or flexible endoscopes. This paper introduces a novel hydraulic actuator based on electrorheological fluid (ERF) as a pivotal advancement in bridging the existing gap within the realm of endoscopy. Following a comprehensive introduction that briefly outlines the electrorheological effect, the subsequent section is dedicated to the elucidation of the actuator’s development process. Challenges arise, particularly in terms of miniaturization and the realization of a hydraulically sealed system with integrated valve electrodes. An internal electrorheological valve system consisting of four valves that are controlled using a pulse-width modulated high voltage was suitable for position control of the antagonistic hydraulic actuators. High-precision stereolithography (SLA) printing has proven practical for manufacturing the actuator components. For functional testing, a test bench was set up in which the actuator follows a setpoint through a PI control loop. The control deviation ranged from 0.6 to 1 degree, with a response time between 6 and 8 seconds. The experiments have demonstrated that, through the use of ERF and integrated valve electrodes, a miniaturized functional actuator can be constructed.

Exploring the fundamental mechanisms of locomotion extends beyond mere simulation and modeling. It necessitates the utilization of physical test benches to validate hypotheses regarding real-world applications of locomotion. This study introduces cost-effective modular robotic platforms designed specifically for investigating the intricacies of locomotion and control strategies. Expanding upon our prior research in Electric-Pneumatic Actuation (EPA), we present the mechanical and electrical designs of the latest developments in the EPA robot series. These include EPA Jumper, a human-sized segmented monopod robot, and its extension EPA Walker, a human-sized bipedal robot. Both replicate the human weight and inertia distributions, featuring co-actuation through electrical motors and pneumatic artificial muscles. These low-cost modular platforms, with considerations for degrees of freedom and redundant actuation, 1) provide opportunities to study different locomotor subfunctions— stance, swing, and balance; 2) help investigate the role of actuation schemes in tasks such as hopping and walking; and 3) allow testing hypotheses regarding biological locomotors in real-world physical test benches.

The effects of the coolant pulsation and the film cooling with the plasma aerodynamic actuation (PAA) could be herein explored via large eddy simulations. The electrohydrodynamic force derived from the PAA was solved through the phenomenological plasma model. The Strouhal number of the sinusoidal coolant pulsation and the averaged pulsation blowing ratio were 0.25 and 1.0, respectively. Comprehensive analyses were carried out on the time-averaged flow fields, and the results revealed that the pulsed cooling jet might cause a deeper penetration into the crossflow, and this phenomenon could be remarkably mitigated by the downward force of the PAA. Furthermore, because of the coolant pulsation, the counter rotating vortex pair (CRVP) expanded to lifted off the wall less well, and the PAA lessened the negative lift-off impact and entrapment from the CRVP. Then, the spatial-temporal development of the coherent structures was figured out by the alterations of the centerline temperature, reflecting formation of the intermittent coherent structures rather than hairpin vortices due to the coolant pulsation, and their size and upcast behaviors were reduced by the PAA. Consequently, there was a basic suppression of the turbulent mixing of the cooling fluid with the crossflow. Finally, the three-dimensional streamlines confirmed that the coherent structure dynamic behaviors were significantly regulated by the PAA for alleviating the adverse influences of the coolant pulsation. In summary, through controlling how the dominating coherent structures evolve throughout time and space, the PAA can effectively increase the pulsed film cooling efficiency.

Emerging soft actuators with various soft materials and traveling-wave motion have been frequently discussed. Various configurations and the resulting performances have been proposed, and it is very challenging for soft actuators in realizing large strokes. This study presents an experimentally validated nonlinear finite element model to predict the deformation produced by a spiral pneumatic rubber actuator to generate traveling-wave motion. The actuator consists of a membrane mounted on a rubber substrate with three air chambers in a spiral configuration, simplifying the actuator's structure. The sequential deformations of the successive chambers interact with each other and produce radial traveling-waves on the membrane surface, driving the objects placed on the actuator. Finite element analysis using ANSYS computer software analyzed the elastic movement by considering the influence of different initial structural types. The structure with three different length ratios was introduced using the four parameters: membrane thickness, chamber width, chamber depth, and wall thickness. The simulation results indicated an optimal structure with specific ratios. A reasonable correlation was obtained during experimental validation; the predicted displacement values were approximately 17% smaller than the experimental values. Finally, the transportation performance of the prototype was tested and a velocity of 2.28 mm/s in the desired direction was achieved. We expect that our demonstration will expand the range of applications of the spiral pneumatic rubber actuator to include conveying or worm-like robots.

Atmospheric stability affects wind turbine wakes significantly. High-fidelity approaches such as large eddy simulations (LES) with the actuator line (AL) model which predicts detailed wake structures, fail to be applied in wind farm engineering applications due to its expensive cost. In order to make wind farm simulations computationally affordable, this paper proposes a new actuator disk model (AD) based on the blade element method (BEM) and combined with Reynolds-averaged Navier–Stokes equations (RANS) to model turbine wakes under different atmospheric stability conditions. In the proposed model, the upstream reference velocity is firstly estimated from the disk averaged velocity based on the one-dimensional momentum theory, and then is used to evaluate the rotor speed to calculate blade element forces. Flow similarity functions based on field measurement are applied to limit wind shear under strongly stable conditions, and turbulence source terms are added to take the buoyant-driven effects into consideration. Results from the new AD model are compared with field measurements and results from the AD model based on the thrust coefficient, the BEM-AD model with classical similarity functions and a high-fidelity LES approach. The results show that the proposed method is better in simulating wakes under various atmospheric stability conditions than the other AD models and has a similar performance to the high-fidelity LES approach however in much lower computational cost.

Memory and emotion are highly vulnerable to psychiatric disorders like post-traumatic stress disorder (PTSD), which has been linked to serotonin (5-HT) metabolism disruptions. In fact, over 90% of the 5-HT precursor tryptophan (Trp) is metabolized via the Trp-kynurenine (KYN) meta-bolic pathway, producing a variety of bioactive molecules. The aadat (kat2) gene encodes mito-chondrial kynurenine aminotransferase (KAT) isotype 2, responsible for kynurenic acid (KYNA) production. Little is known about its role in behavior. In CRISPR/Cas9-induced aadat knockout (kat2−/−) mice, we examined the effects on emotion, memory, motor function, Trp and its metabolite levels, enzyme activities in the plasma and the urine of 8-week-old males compared to wild-type mice. Transgenic mice showed more depressive-like behaviors in the forced swim test, but not in the tail suspension, anxiety, or memory tests. They also had fewer center field and corner entries, shorter walking distances, and fewer jumping counts in the open field test. Plasma metabolite levels are generally consistent with those of urine: KYN, antioxidant KYNs, 5-hydroxyindolacetic acid, and indole-3-acetic acid levels are lower; enzyme activities in KATs, kynureninase, and monoamine oxidase/aldehyde dehydrogenase are lower, but kynurenine 3-monooxygenase is higher; and ox-idative stress and excitotoxicity indices are higher. Transgenic mice show depression-like behavior in a learned helplessness model, emotional indifference, and motor deficits, coupled with a decrease in KYNA, a shift of Trp metabolism toward the KYN-3-HK pathway, and a partial decrease in the gut microbial Trp-indole pathway metabolite. This is the first evidence that deleting the aadat gene causes depression-like behaviors that are unique to despair experience, which appears to be linked to excitatory neurotoxic and oxidative stresses. This may lead to the development of a double-hit preclinical model in experience-based depression, better understanding of these complex condi-tions, and more effective therapeutic strategies by elucidating the relationship between Trp me-tabolism and PTSD pathogenesis.

A comprehensive modeling framework for the thermoforming of polymer matrix woven laminate composite was developed. Two numerical indicators, the slip path length and traction magnitude, have been identified to be positively correlated to matrix smearing and wrinkling defects. The material model has been calibrated with picture-frame experimental results, and the prediction accuracy for intra-ply shear and thickness distribution were examined with measurements on the physically formed parts. Finally, a parametric study was conducted to determine the relationship between various process parameters and the quality of the formed part. For the trapezoidal part, orienting the laminate at 45-degrees to the mold axis reduces the likelihood of matrix smear and wrinkling defects. Although this laminate orientation yielded a greater spatial variation of part thickness, the thickness deviation is lower than that for the 0-degree orientation case. Higher forming rates were found to result in more defects due to increased slip path lengths and traction magnitudes. Optimal forming speeds should balance rapid shaping within the operating temperature window while avoiding tear. It was discovered that shallower molds benefit from faster ramp rates, while deeper molds require slower rates to manage extensive shearing, stretching, and bending. Faster forming rates lead to smaller thickness increases at high intra-ply shear regions, indicating a shift from intra-ply shear to out-of-plane bending due to the visco-plastic effect of the molten laminate, and can negatively impact part quality. Lastly, it was shown that a well-conceived strategy using darts could improve the part quality by reducing the magnitude of the defect indicators.

Urban rail transit hub platform is the most important area for passenger flow distribution. In order to calculate passenger flow volume in platform and evaluate platform service level during rush hours, this paper presents a method for modeling and simulation of passenger flow distribution in platform. Passenger flow distribution model (PFDM) is proposed based on the basic analysis and the superposition principle of passenger flow. Simulation design for PFDM is proposed by Anylogic, which contains simulation process and simulation model. Experiment results show that PFDM and simulation design are effective and accordant with the reality scenario, and the simulation precision is comparatively ideal. This research could provide a beneficial reference for train scheduling and operation management under the viewpoint of traffic safety and service level.

This study investigates the diversity and evolution of research topics within the dental sciences from 1994 to 2023 using topic modeling and Shannon's entropy as a measure of research diversity. We analyzed a dataset of 412036 scientific articles across six dental disciplines: Orthodontics, Pros-thodontics, Periodontics, Implant Dentistry, Oral Surgery, and Restorative Dentistry. This research relies on BERTopic to identify distinct topics within each field. The study revealed significant shifts in research focus over time, with some disciplines exhibiting robust growth in article numbers such as Periodontics and Prosthodontics. The application of Shannon's entropy revealed an increasing diversification of research efforts in disciplines such as Restorative Dentistry, while others, like Prosthodontics, in spite of their size and their high number of research topics, maintain a more specialized research focus. Taken together, our findings describe the dynamic nature of dental re-search and highlight the balance shifts in research focus across several key areas of Dentistry.

Our skin epidermis constitutes the most important innate defense barrier against all pathogens. Therefore, even if skin lesions are common due to infections, scarring, genetic disorders, and other diseases, skin integrity is crucial for maintaining body homeostasis. Marine collagen peptides (MCPs) and Glycosaminoglycans (GAGs) have been described as potential wound healing (WH) agents. Recently, through an ex vivo clinical approach, we have demonstrated the nutricosmetic potential of fish cartilage hydrolysate (FCH), which presents a combination of collagen peptides and GAGs. Here, we coupled a clinical approach with in vitro experiments on human dermal fibroblasts (HDFs) and applied a Data Independent Acquisition - Parallel Accumulation Serial Fragmentation (diaPASEF) proteomic analysis, to assess the potential benefit of FCH in WH and its mode of action. Our results show that human serum enriched with circulating metabolites resulting from FCH ingestion, improved wound closure in scratch assays. In support, some proteins with anti-inflammatory and immunomodulatory properties or prone to promote hydration and extracellular matrix (ECM) stability showed increased expression in HDFs, after exposure to FCH-enriched serum. These findings suggest that FCH appears as a promising nutrient for WH and skin regeneration.

The strictness of the result of an excavation, whether mechanical or by means of explosives, is naturally conditioned by the objective, and therefore by the type of technique applied to achieve it. To attain the best results in terms of rock breakage and respect of the final profile, it’s important to evaluate the excavation specific energy and its optimization. This research focuses on evaluating the effects of different techniques on the quality of final walls in open-pit and underground operations. Different geometries and configurations can be applied to both quarrying and tunnelling blasts. The research is aimed to push contour blasts to their limits, and the main aspects are discussed in order to improve the blast parameters in the daily practice.

Chemical vapor deposition (CVD) is a vital process for depositing thin films of various materials with precise control over thickness, composition, and properties. Understanding the heat and mass transfer mechanisms during CVD is essential for optimizing process parameters and ensuring high-quality film deposition. This review provides an overview of recent advancements in the heat and mass transfer modeling for chemical vapor deposition processes. It explores innovative modeling techniques, recent research findings, emerging applications, and challenges in the field. Additionally, it discusses future directions and potential areas for further advancement in CVD modeling.

Electrical contacts are important circuit components with diverse industrial applications, and their failure can lead to multiple unwanted effects. Hence, the behavior of electrical contacts is a widely studied topic in scientific literature based on various approaches, tools, and techniques. The present study proposes a numerical modeling and simulation approach based on the Holm contact theory to study the dependence between the electric potential and the temperature within an electrical contact. Structured in 5 sections, the research was conducted using COMSOL Multiphysics software and its solid-state mechanics, electric current, and heat transfer modules in order to highlight contact behavior from mechanical, electrical and thermal points of view: the von Mises stress, contact force, the electric field amplitude, the variation of the electrical potential along the current path, the temperature gradient, and dependence of temperature along the contact elements edges were obtained by simulation and graphically represented. The results are in line with the expectations and with past research that was studied in the literature review.

Advanced Finite Element (FE) modeling and simulations were performed on vehicular crashes into a Three-bar Metal Bridge Rail (TMBR). The FE models of a sedan, a pickup truck, and a TMBR section were adopted in the crash simulations subject to Manual for Assessing Safety Hardware (MASH) Test Level 2 (TL-2) and Test Level 3 (TL-3) requirements. The test vehicle models were first validated using full-scale physical crash tests conducted on a two-bar metal bridge using a sedan and a pickup truck with similar overall physical properties and sizes to their respective vehicles used in the simulations. The validated vehicular models were then used to evaluate the crash performance of the TMBR using MASH Evaluation Criteria for structural adequacy, occupant risk, and post-impact trajectory. The TMBR met all MASH TL-2 requirements but failed to meet the MASH TL-3 Criteria H and N requirements when impacted by the sedan. The TMBR was also evaluated under in-service conditions (behind a 1.52-m wide sidewalk) and impacted by the sedan under MASH TL-3 conditions. The simulation results showed that the TMBR behind a sidewalk met all safety requirements except for the occupant impact velocity in the longitudinal direction, which exceeded the MASH limit by 3.93%.

Research on piezo-composite actuators has been actively conducted over the past two decades as a response to strong demand for light, compact actuators to replace electro-magnetic motor actuators in micro robots, small flying drones, and compact missile systems. Layered piezo-composite unimorph actuators have been studied to provide active vibration control of thin-walled aerospace structures, control the shapes of aircraft wing airfoils, and control the fins of small missiles, because they require less space and provide better frequency responses than conventional electro-magnetic motor actuator systems. However, based on the limited actuation strains of conventional piezo-composite unimorph actuators with poly-crystalline piezoelectric ceramic layers, they have not been implemented effectively as actuators for small aerospace vehicles. In this study, a lightweight piezo-composite unimorph actuator (LIPCA-S2) was manufactured and analyzed to predict its flexural actuation displacement. It was found that the actuated tip displacement of a piezo-composite cantilever could be predicted accurately using the proposed prediction model based on the nonlinear properties of the piezoelectric strain coefficient and elastic modulus of a piezoelectric single crystal.

Aim: Ovarian cancer is the leading cause of gynecological cancer deaths worldwide. Treatment methods are listed as surgery, chemotherapy and radiotherapy depending on the stage of the cancer, but developing resistance to chemotherapy increases the need for alternative agents that act on the same pathways. In this study, the effects of rosmarinic acid (RA) and doxorubicin (DX) on the activation of FOXP3, an important tumor suppressor gene, in OVCAR3 cells were examined. Material Method: In the study, human ovarian adenocarcinoma cell line was used. MTT test was applied to determine the effect of rosmarinic acid and doxorubicin on the proliferation of OVCAR3 cells. Expression levels of FOXP3 for cell proliferation and Capase-3 for Apoptosis were determined by qRT-PCR and Western blot analysis. Wound healing model was applied to determine metastasis. The results were evaluated with one-way ANOVA in SPSS 20.0 program as p≤0.05. Results: It was determined that rosmarinic acid alone and in combination with doxorubicin inhibited the proliferation of OVCAR3 cells in a time- and dose-dependent manner for 24, 48 and 72 hours, and caused the cells to die by causing them to undergo apoptosis. It was observed that Caspase-3 expression increased approximately tenfold in OVCAR3 cells, while FOXP3 expression increased only in RA treatment and was downregulated in DX and RA+DX treatments. Coclusion According to the results of our study, it was observed that many steps of the signaling pathways related to proliferation, migration and apoptosis were affected by the combination of RA and DX in OVCAR3 cells. This shows that RA will gain an important place in cancer treatment with more comprehensive studies.

Our recent analysis of empirical limit order flow data in financial markets reveals a power-law distribution in limit order cancellation times. These times are modeled using a discrete probability mass function derived from the Tsallis q-exponential distribution, closely aligned with the second form of the Pareto distribution. We elucidate this distinctive power-law statistical property through the lens of agent heterogeneity in trading activity and asset possession. Our study introduces a novel modeling approach that combines fractional Lévy stable motion for limit order inflow with this power-law distribution for cancellation times, significantly enhancing the prediction of order imbalances. This model not only addresses gaps in current financial market modeling but also extends to broader contexts such as opinion dynamics in social systems, capturing the finite lifespan of opinions. Characterized by stationary increments and a departure from self-similarity, our model provides a unique framework for exploring long-range dependencies in time series. This work paves the way for more precise financial market analyses and offers new insights into the dynamic nature of opinion formation in social systems.

The paper presents two procedures for creating 3D discrete models of apple using the finite element method (FEM). The study focused on a new Polish apple variety, Chopin at development, ripening, and senescence maturity stages. The analysis of the results allowed for the determination that, depending on the desired outcomes, the parenchymal tissue can be considered as a material with either elastic or elastoplastic properties. Model validation was performed using displacement-force relationships and changes in contact area as a function of loading force obtained from compression tests. Elastoplastic models reflect empirical studies much better. The fit of the elastic models, based on force vs. displacement curves, ranged from 79% to 83%, while the fit of the elastoplastic models to empirical data ranged from 91% to 96%. Elastic models, on the other hand, are well-suited to the modified force vs. displacement curves, which reflect the elastic behavior of apples under compression test. Contour plots of pressures for elastoplastic models align much better with the test results than those for elastic models. 4. Similarly, in the case of contact area values, the elastoplastic models outperformed the elastic models, achieving a fit between 92% and 96%, while the elastic models reached only 82% to 83% compliance.

Driving simulators are widely used for understanding human-machine interaction, driver behavior and in driver training. The effectiveness of simulators in these process depends largely on their ability to generate realistic motion cues. Though the conventional filter-based motion cueing strategies have provided reasonable results, these methods suffer from poor workspace management. To address this issue, linear MPC-based strategies have been applied in the past. However, since the kinematics of the motion platform itself is non-linear and the required motion varies with the driving conditions, this approach tends to produce sub-optimal results. This paper presents a nonlinear MPC-based algorithm which incorporates the nonlinear kinematics of the Stewart platform within the MPC algorithm in order to increase the cueing fidelity and utilize maximum workspace. Further, adaptive weights-based tuning is used to smoothen the movement of the platform towards its physical limits. Full-track simulations were carried out and performance indicators were defined to objectively compare the response of the proposed algorithm with classical washout filter and linear MPC-based algorithms. The results indicate a better reference tracking with lower root mean square error and higher shape correlation for the proposed algorithm. Lastly, the effect of the adaptive weights-based tuning was also observed in the form of smoother actuator movements and better workspace utilization.

A power factor correction (PFC) rectifier is compulsory for any electronic circuitry connected to the electrical grid. The majority of PFCs that are utilized are based on a step-up converter that supplies high DC voltage at its output terminal. Electric vehicle battery voltage varies from a few hundred to almost a thousand volts. Thus, an additional conversion step is obligatory when designing an all-brand universal charger. This paper presents a new type of front-end versatile step up / down three voltage level PFC. The rectifier can operate in continuous conduction mode or discontinuous conduction mode. First, the rectifier’s principle of operation is described, and then an innovative rectifier is analyzed for continuous and discontinuous conduction modes. Finally, the proposed theory is experimentally validated in a multiplier-less dual loop mode at discontinuous conduction modes. It was shown that although there is no multiplier use in the control circuitry, the power factor is near unity. It was revealed that the rectifier could swing the output voltage from 50 V to 900 V while the input voltage was 230 Vrms. The innovative topology suits any standard PFC rectifier, three-level voltage supplement, and dual-stage low-voltage power supply.